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Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A
  Review

Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review

20 December 2018
Juan J. Cerrolaza
M. L. Picazo
L. Humbert
Yoshinobu Sato
Daniel Rueckert
M. A. G. Ballester
M. Linguraru
    AI4CE
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Papers citing "Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review"

11 / 11 papers shown
Title
Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes
Mesh2SSM++: A Probabilistic Framework for Unsupervised Learning of Statistical Shape Model of Anatomies from Surface Meshes
Krithika S. Iyer
Mokshagna Sai Teja Karanam
Shireen Elhabian
64
0
0
11 Feb 2025
S3M: Scalable Statistical Shape Modeling through Unsupervised
  Correspondences
S3M: Scalable Statistical Shape Modeling through Unsupervised Correspondences
Lennart Bastian
Alexander Bauman
Emily Hoppe
Vincent Burgin
Ha Young Kim
Mahdi Saleh
Benjamin Busam
Nassir Navab
24
8
0
15 Apr 2023
Multi-organ segmentation: a progressive exploration of learning
  paradigms under scarce annotation
Multi-organ segmentation: a progressive exploration of learning paradigms under scarce annotation
Shiman Li
Haoran Wang
Yucong Meng
Chenxi Zhang
Zhijian Song
32
6
0
07 Feb 2023
Multi-center anatomical segmentation with heterogeneous labels via
  landmark-based models
Multi-center anatomical segmentation with heterogeneous labels via landmark-based models
Nicolás Gaggion
Maria Vakalopoulou
Diego H. Milone
Enzo Ferrante
33
5
0
14 Nov 2022
A Review on Deep-Learning Algorithms for Fetal Ultrasound-Image Analysis
A Review on Deep-Learning Algorithms for Fetal Ultrasound-Image Analysis
M. C. Fiorentino
Francesca Pia Villani
M. D. Cosmo
Emanuele Frontoni
S. Moccia
21
101
0
28 Jan 2022
Medical Image Segmentation Using Deep Learning: A Survey
Medical Image Segmentation Using Deep Learning: A Survey
Risheng Wang
Tao Lei
Xiaogang Du
Yong Wan
Hongying Meng
A. Nandi
SSeg
OOD
33
544
0
28 Sep 2020
A review of deep learning in medical imaging: Imaging traits, technology
  trends, case studies with progress highlights, and future promises
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
S. Kevin Zhou
H. Greenspan
Christos Davatzikos
James S. Duncan
Bram van Ginneken
A. Madabhushi
Jerry L. Prince
Daniel Rueckert
Ronald M. Summers
55
624
0
02 Aug 2020
CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation
CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation
A. Emre Kavur
N. Gezer
M. Baris
Sinem Aslan
Pierre-Henri Conze
...
Klaus H. Maier-Hein
G. Akar
Gözde B. Ünal
O. Dicle
M. Alper Selver
50
611
0
17 Jan 2020
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
Christian Wachinger
M. Reuter
T. Klein
3DV
40
330
0
27 Feb 2017
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
295
10,618
0
19 Feb 2017
Hough-CNN: Deep Learning for Segmentation of Deep Brain Regions in MRI
  and Ultrasound
Hough-CNN: Deep Learning for Segmentation of Deep Brain Regions in MRI and Ultrasound
Fausto Milletari
Seyed-Ahmad Ahmadi
Christine Kroll
A. Plate
Verena E. Rozanski
...
J. Levin
O. Dietrich
B. Ertl-Wagner
K. Boetzel
Nassir Navab
200
363
0
26 Jan 2016
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